Implement Tries in Python
Problem Statement
A trie (pronounced as “try”) or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker.
Implement the Trie class:
- Trie() Initializes the trie object.
- def insert(String word) Inserts the string word into the trie.
- def search(String word) Returns true if the string word is in the trie (i.e., was inserted before), and false otherwise.
- def startsWith(String prefix) Returns true if there is a previously inserted string word that has the prefix prefix, and false otherwise.
Example 1:
Input [“Trie”, “insert”, “search”, “search”, “startsWith”, “insert”, “search”] [[], [“apple”], [“apple”], [“app”], [“app”], [“app”], [“app”]]
Output
[null, null, true, false, true, null, true]
Explanation
Trie trie = new Trie();
trie.insert(“apple”);
trie.search(“apple”); // return True
trie.search(“app”); // return False
trie.startsWith(“app”); // return True
trie.insert(“app”);
trie.search(“app”); // return True
Constraints:
1 <= word.length, prefix.length <= 2000
word and prefix consist only of lowercase English letters.
At most 3 * 104 calls in total will be made to insert, search, and startsWith.
class TrieNode:
'''
Not storing the node itself in the TrieNode class. Will be implicit from the HashMap.Example - children["a"] = TrieNode()
'''
def __init__(self):
self.children = {}
self.endOfWord = False # applicable for every node
class Trie:
def __init__(self):
self.root = TrieNode()
def insert(self, word):
'''
Insert the word in the tree
'''
cur = self.root
for w in word:
if not w in cur.children():
cur.children[w] = TrieNode()
cur = cur.children[w]
cur.endOfWord = True
def search(self, word):
cur = self.root
for w in word:
if not word in cur.children:
return False
cur = cur.children[w]
return cur.endOfWord
def startsWith(self, prefix):
cur = self.root
for p in prefix:
if not p in cur.children:
return False
cur = cur.children[w]
return True
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